{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Visualize Parameter Space with Exhaustive Optimizer\n",
    "\n",
    "ITK optimizers are commonly used to select suitable values for various parameters, such as choosing how to transform a moving image to register with a fixed image. A variety of image metrics and transform classes are available to guide the optimization process, each of which may employ parameters unique to its own implementation. It is often useful to visualize how changes in parameters will impact the metric value and the optimization process.\n",
    "\n",
    "The `ExhaustiveOptimizer` class exists to evaluate a metric over a windowed parameter space of fixed step size. This example shows how to use `ExhaustiveOptimizerv4` with the `MeanSquaresImageToImageMetricv4` metric and `Euler2DTransform` transform to survey performance over a parameter space and visualize the results with `matplotlib`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "import os\n",
    "import sys\n",
    "import itertools\n",
    "from math import pi, sin, cos, sqrt\n",
    "from urllib.request import urlretrieve\n",
    "\n",
    "import matplotlib.pyplot as plt\n",
    "import numpy as np\n",
    "\n",
    "import itk\n",
    "from itkwidgets import view, compare, checkerboard, cm\n",
    "\n",
    "module_path = os.path.abspath(os.path.join(\".\"))\n",
    "\n",
    "if module_path not in sys.path:\n",
    "    sys.path.append(module_path)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Get sample data to register\n",
    "\n",
    "In this example we seek to transform an image of an orange to overlay on the image of an apple. We will eventually use the `MeanSquaresImageToImageMetricv4` class to inform the optimizer about how the two images are related given the current parameter state. We can visualize the fixed and moving images with `ITKWidgets`."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [],
   "source": [
    "fixed_img_path = \"apple.jpg\"\n",
    "moving_img_path = \"orange.jpg\"\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "if not os.path.exists(fixed_img_path):\n",
    "    url = \"https://data.kitware.com/api/v1/file/5cad1aec8d777f072b181870/download\"\n",
    "    urlretrieve(url, fixed_img_path)\n",
    "if not os.path.exists(moving_img_path):\n",
    "    url = \"https://data.kitware.com/api/v1/file/5cad1aed8d777f072b181879/download\"\n",
    "    urlretrieve(url, moving_img_path)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "fixed_img = itk.imread(fixed_img_path, itk.F)\n",
    "moving_img = itk.imread(moving_img_path, itk.F)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.jupyter.widget-view+json": {
       "model_id": "41b1cf3266494894b08c3fc049f48df3",
       "version_major": 2,
       "version_minor": 0
      },
      "text/plain": [
       "AppLayout(children=(HBox(children=(Label(value='Link:'), Checkbox(value=False, description='cmap'), Checkbox(v…"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "compare(fixed_img, moving_img, ui_collapsed=True)\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Define and Initialize the Transform\n",
    "\n",
    "In this example we will use an `Euler2DTransform` instance to represent how the moving image will be sampled from the fixed image. The [Euler2DTransform](https://itk.org/Doxygen/html/classitk_1_1Euler2DTransform.html) documentation shows that the transform has three parameters, first a rotation around a fixed center, followed by a 2D translation. We use a `CenteredTransformInitializer` to estimate what may be a \"good\" fixed center point at which to define the transform prior to conducting optimization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {},
   "outputs": [],
   "source": [
    "dimension = 2\n",
    "FixedImageType = itk.Image[itk.F, dimension]\n",
    "MovingImageType = itk.Image[itk.F, dimension]\n",
    "TransformType = itk.Euler2DTransform[itk.D]\n",
    "OptimizerType = itk.ExhaustiveOptimizerv4[itk.D]\n",
    "MetricType = itk.MeanSquaresImageToImageMetricv4[FixedImageType, MovingImageType]\n",
    "TransformInitializerType = itk.CenteredTransformInitializer[\n",
    "    itk.MatrixOffsetTransformBase[itk.D, 2, 2], FixedImageType, MovingImageType\n",
    "]\n",
    "RegistrationType = itk.ImageRegistrationMethodv4[FixedImageType, MovingImageType]\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [],
   "source": [
    "transform = TransformType.New()\n",
    "\n",
    "initializer = TransformInitializerType.New(\n",
    "    Transform=transform,\n",
    "    FixedImage=fixed_img,\n",
    "    MovingImage=moving_img,\n",
    ")\n",
    "initializer.InitializeTransform()\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Run Optimization\n",
    "\n",
    "We rely on the `ExhaustiveOptimizerv4` class to visualize the parameter space. For this example we choose to visualize the metric value over the first two parameters only, so we set the number of steps in the third dimension to zero. The angle and translation parameters are measured on different scales, so we set the optimizer to take steps of reasonable size along each dimension. An observer is used to save the results of each step."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [],
   "source": [
    "metric_results = dict()\n",
    "\n",
    "metric = MetricType.New()\n",
    "optimizer = OptimizerType.New()\n",
    "\n",
    "optimizer.SetNumberOfSteps([10, 10, 0])\n",
    "\n",
    "scales = optimizer.GetScales()\n",
    "scales.SetSize(3)\n",
    "scales.SetElement(0, 0.1)\n",
    "scales.SetElement(1, 1.0)\n",
    "scales.SetElement(2, 1.0)\n",
    "optimizer.SetScales(scales)\n",
    "\n",
    "\n",
    "def collect_metric_results():\n",
    "    metric_results[tuple(optimizer.GetCurrentPosition())] = optimizer.GetCurrentValue()\n",
    "\n",
    "\n",
    "optimizer.AddObserver(itk.IterationEvent(), collect_metric_results)\n",
    "\n",
    "registration = RegistrationType.New(\n",
    "    Metric=metric,\n",
    "    Optimizer=optimizer,\n",
    "    FixedImage=fixed_img,\n",
    "    MovingImage=moving_img,\n",
    "    InitialTransform=transform,\n",
    "    NumberOfLevels=1,\n",
    ")\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "MinimumMetricValue: 8195.5765\tMaximumMetricValue: 13799.5822\n",
      "MinimumMetricValuePosition: [0.0, 0.0, 0.0]\tMaximumMetricValuePosition: [0.6000000000000001, 10.0, 0.0]\n",
      "StopConditionDescription: ExhaustiveOptimizerv4: Completed sampling of parametric space of size 3\t\n"
     ]
    }
   ],
   "source": [
    "registration.Update()\n",
    "\n",
    "print(\n",
    "    f\"MinimumMetricValue: {optimizer.GetMinimumMetricValue():.4f}\\t\"\n",
    "    f\"MaximumMetricValue: {optimizer.GetMaximumMetricValue():.4f}\\n\"\n",
    "    f\"MinimumMetricValuePosition: {list(optimizer.GetMinimumMetricValuePosition())}\\t\"\n",
    "    f\"MaximumMetricValuePosition: {list(optimizer.GetMaximumMetricValuePosition())}\\n\"\n",
    "    f\"StopConditionDescription: {optimizer.GetStopConditionDescription()}\\t\"\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize Parameter Space as 2D Scatter Plot\n",
    "\n",
    "We can use `matplotlib` to view the results of each discrete optimizer step as a 2D scatter plot. In this case the horizontal axis represents the angle that the image is rotated about its fixed center in radians and the vertical axis represents the horizontal distance that the image is translated after rotation. The value of `MeanSquaresImageToImageMetricv4` for each transformation is represented via color gradients. We can also directly plot optimizer extrema for visualization."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 10,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "[<matplotlib.lines.Line2D at 0x19ced452370>]"
      ]
     },
     "execution_count": 10,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = plt.axes()\n",
    "ax.scatter(\n",
    "    [x[0] for x in metric_results.keys()],\n",
    "    [x[1] for x in metric_results.keys()],\n",
    "    c=list(metric_results.values()),\n",
    "    cmap=\"coolwarm\",\n",
    ")\n",
    "ax.plot(\n",
    "    optimizer.GetMinimumMetricValuePosition().GetElement(0),\n",
    "    optimizer.GetMinimumMetricValuePosition().GetElement(1),\n",
    "    \"wx\",\n",
    ")\n",
    "ax.plot(\n",
    "    optimizer.GetMaximumMetricValuePosition().GetElement(0),\n",
    "    optimizer.GetMaximumMetricValuePosition().GetElement(1),\n",
    "    \"k^\",\n",
    ")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Visualize Parameter Space as 3D Surface\n",
    "\n",
    "We can also plot results in 3D space with `numpy` and `matplotlib`. In this example we use `np.meshgrid` to define the parameter domain and define corresponding metric results as an accompanying `numpy` array. The resulting graph can be used to visualize gradients and visually identify extrema."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 11,
   "metadata": {},
   "outputs": [],
   "source": [
    "x_unique = list(set(x for (x, y, _) in metric_results.keys()))\n",
    "y_unique = list(set(y for (x, y, _) in metric_results.keys()))\n",
    "x_unique.sort()\n",
    "y_unique.sort()\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 12,
   "metadata": {},
   "outputs": [],
   "source": [
    "X, Y = np.meshgrid(x_unique, y_unique)\n",
    "Z = np.array([[metric_results[(x, y, 0)] for x in x_unique] for y in y_unique])\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 13,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(21, 21)"
      ]
     },
     "execution_count": 13,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "np.shape(Z)\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 14,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<mpl_toolkits.mplot3d.art3d.Poly3DCollection at 0x19ced539fa0>"
      ]
     },
     "execution_count": 14,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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\n",
      "text/plain": [
       "<Figure size 432x288 with 1 Axes>"
      ]
     },
     "metadata": {
      "needs_background": "light"
     },
     "output_type": "display_data"
    }
   ],
   "source": [
    "fig = plt.figure()\n",
    "ax = fig.gca(projection=\"3d\")\n",
    "\n",
    "ax.plot_surface(X, Y, Z, cmap=\"coolwarm\")\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Clean up"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 15,
   "metadata": {},
   "outputs": [],
   "source": [
    "os.remove(fixed_img_path)\n",
    "os.remove(moving_img_path)\n"
   ]
  }
 ],
 "metadata": {
  "kernelspec": {
   "display_name": "Python 3",
   "language": "python",
   "name": "python3"
  },
  "language_info": {
   "codemirror_mode": {
    "name": "ipython",
    "version": 3
   },
   "file_extension": ".py",
   "mimetype": "text/x-python",
   "name": "python",
   "nbconvert_exporter": "python",
   "pygments_lexer": "ipython3",
   "version": "3.8.5"
  }
 },
 "nbformat": 4,
 "nbformat_minor": 4
}
